Decorous lower bounds for minimum linear arrangement

Minimum Linear Arrangement is a classical basic combinatorial optimization problem from the 1960s, which turns out to be extremely challenging in practice. In particular, for most of its benchmark instances, even the order of magnitude of the optimal solution value is unknown, as testified by the surveys on the problem that contain tables in which the best known solution value often has one more digit than the best known lower bound value. In this paper, we propose a linear-programming based approach to compute lower bounds on the optimum. This allows us, for the first time, to show that the best known solutions are indeed not far from optimal for most of the benchmark instances

A Branch-and-Cut Algorithm for the Capacitated Open Vehicle Routing Problem

In open vehicle routing problems, the vehicles are not required to return to the depot after completing service. In this paper, we present the first exact optimization algorithm for the open version of the well-known capacitated vehicle routing problem (CVRP). The algorithm is based on branch-and-cut. We show that, even though the open CVRP initially looks like a minor variation of the standard CVRP, the integer programming formulation and cutting planes need to be modified in subtle ways. Computational results are given for several standard test instances, which enables us for the first time to assess the quality of existing heuristic methods, and to compare the relative difficulty of open and closed versions of the same problem.Vehicle routing; branch-and-cut; separation

On Linearising Mixed-Integer Quadratic Programs via Bit Representation

It is well known that, under certain conditions, one can use bit representation to transform both integer quadratic programs and mixed-integer bilinear programs into mixed-integer linear programs (MILPs), and thereby render them easier to solve using standard software packages. We show how to convert a more general family of mixed-integer quadratic programs to MILPs, and present several families of strong valid linear inequalities that can be used to strengthen the continuous relaxations of the resulting MILPs

A Binarisation Heuristic for Non-Convex Quadratic Programming with Box Constraints

Non-convex quadratic programming with box constraints is a fundamental problem in the global optimization literature, being one of the simplest NP-hard nonlinear programs. We present a new heuristic for this problem, which enables one to obtain solutions of excellent quality in reasonable computing times. The heuristic consists of four phases: binarisation, convexification, branch-and-bound, and local optimisation. Some very encouraging computational results are given

Bit Representation Can Improve SDP Relaxations of Mixed-Integer Quadratic Programs

A standard trick in integer programming is to replace bounded integer variables with binary variables, using a bit representation. In a previous paper, we showed that this process can be used to improve linear programming relaxations of mixed-integer quadratic programs. In this paper, we show that it can also be used to improve {\em semidefinite}\/ programming relaxations

On Laminar Matroids and b-Matchings

We prove that three matroid optimisation problems, namely, the matchoid, matroid parity and matroid matching problems, all reduce to the b-matching problem when the matroids concerned are laminar. We then use this equivalence to show that laminar matroid parity polytopes are affinely congruent to b-matching polytopes, and have Chvátal rank equal to one. On the other hand, we prove that laminar matroid parity polytopes can have facet-defining inequalities that have left-hand side coefficients greater than 2

Projection results for the k-partition problem

The k-partition problem is an NP-hard combinatorial optimisation problem with many applications. Chopra and Rao introduced two integer programming formulations of this problem, one having both node and edge variables, and the other having only edge variables. We show that, if we take the polytopes associated with the ‘edge-only’ formulation, and project them into a suitable subspace, we obtain the polytopes associated with the ‘node-and-edge’ formulation. This result enables us to derive new valid inequalities and separation algorithms, and also to shed new light on certain SDP relaxations. Computational results are also presented